What We Know About America’s Billionaires: 1,135 and Counting

“Billionaire” evokes tech founders such as Jeff Bezos or Bill Gates , but there is a large and growing group of people worth at least $1 billion in small towns and big cities that rarely make the headlines.

There were 1,135 billionaires in the U.S. as of 2024—up from 927 in 2020, according to data from Altrata, a wealth-intelligence firm. The biggest concentration, 255 of them, is in California. But the super rich are also behind businesses in places such as Ridgeland, Miss., and Waunakee, Wisc.

Collectively, these people are worth about $5.7 trillion, according to Altrata’s estimates. That’s enough wealth to buy…

While many of these individuals own properties in upscale communities such as Palm Beach, Fla., they also congregate in destinations such as Cashiers, N.C.—a town in the Blue Ridge Mountains where four billionaire families have residences. The smallest town where a billionaire owns property? Winifred, Mont., population 172.

The list of billionaires includes some familiar dynasties, such as the Walmart Waltons and Hyatt Pritzkers. There are also lesser known members of this elite club, such as Diane Hendricks , co-founder of roofing-products distributor ABC Supply, and the heirs to the Russell Stover Chocolates fortune.

The billionaire border can be fuzzy. Markets fluctuate, the value of private companies can be uncertain and big donations dent fortunes, meaning dozens of individuals—even stars such as LeBron James and Beyoncé—can move on or off the list.

The 100 richest billionaires account for nearly $3.86 trillion in wealth—more than half the total. Just three men— Elon Musk , Bezos and Mark Zuckerberg —account for almost $1 trillion of it.

Despite those outsize Silicon Valley fortunes , most U.S.-based billionaires didn’t make their wealth in tech. About 300 came from banking and finance, compared with roughly 110 from the tech sector. Another 75 came from real estate.

A third of billionaires inherited much or all of their wealth, Altrata said. There is just one Rockefeller on the list, but 50 billionaire heirs of five companies hold roughly $830 billion total. These individuals account for nearly 15% of all the billionaires’ wealth. undefined

Billionaires have publicly donated or pledged to give about $185 billion since 2015, according to Altrata. Mostly, they support causes such as education and medical research—they gave $90 billion to those two in the past 10 years. That has given them sway in ongoing campus debates over freedom of speech and antisemitism.

While some billionaires such as Gates and Warren Buffett have openly pledged to give away much of their wealth , others have donated little so far. About a quarter of the billionaires in the list have known donations of less than $1 million in the past decade.

Some give more to organizations they’re tied to. Hedge-fund manager Bill Ackman gave about $120 million to multiple causes, but he gave $1.36 billion to a foundation where he and his wife serve as trustees, which supports medical research and other causes.

Among the top recipients of donations tracked by Altrata are global charities such as the Gates Foundation and Gavi, the Vaccine Alliance.

One of the most popular recipients is the Central Park Conservancy in New York, which received donations from 89 billionaires worth about $100 million.

Johns Hopkins University received $7.5 billion from close to 30 billionaires, but most of it came from Michael Bloomberg , who gave more than $5 billion.

Methodology

The Wall Street Journal analysed data on more than 1,100 individuals provided by Altrata, which estimates net worth by assessing privately and publicly held businesses and investible assets. Altrata’s data on properties includes residences, land parcels and other properties owned in the person’s name. It uses primary business address to determine a billionaire’s location and assigns each billionaire to a primary industry based on their current roles. Altrata adjusts totals to account for shifts in asset values that could push some individuals over or under $1 billion in wealth.

A sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.

The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.

The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.

The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.

This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.

The debt behind the AI build-out

Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.

Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.

JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.

The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.

That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.

A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.

When interest rates rise, those assumptions become less forgiving.

Inflation changes the calculation

September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.

The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.

CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.

Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.

Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.

The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.

China adds another source of pressure

Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.

Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.

The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.

That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.

A reset rather than the end of the boom

The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.

What has changed is the market’s willingness to overlook the price and financing structure of that growth.

The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.

More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.

For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.

Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.

The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.

Fact box

Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026

Philadelphia Semiconductor Index: Down approximately 11.4 per cent

Micron Technology: Down approximately 14.6 per cent

Samsung Electronics: Down approximately 18 per cent

SK Hynix: Down approximately 24 per cent

US September inflation: 3.7 per cent annually

Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion